Intrinsic sensory neurons of the gut (Chambers et al. 2014)

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Accession:155796
A conductance base model of intrinsic neurons neurons in the gastrointestinal tract. The model contains all the major voltage-gated and calcium-gated currents observed in these neurons. This model can reproduce physiological observations such as the response to multiple brief depolarizing currents, prolonged depolarizing currents and hyperpolarizing currents. This model can be used to predict how different currents influence the excitability of intrinsic sensory neurons in the gut.
Reference:
1 . Chambers JD, Bornstein JC, Gwynne RM, Koussoulas K, Thomas EA (2014) A detailed, conductance-based computer model of intrinsic sensory neurons of the gastrointestinal tract. Am J Physiol Gastrointest Liver Physiol 307:G517-32 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Channel/Receptor;
Brain Region(s)/Organism:
Cell Type(s): Gastrointestinal tract intrinsic sensory neuron;
Channel(s): I Na,p; I Na,t; I K,leak; I K,Ca; I CAN; I Mixed; I Na, leak; Ca pump;
Gap Junctions:
Receptor(s):
Gene(s): Nav1.3 SCN3A; Nav1.7 SCN9A; Nav1.9 SCN11A SCN12A;
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Detailed Neuronal Models; Action Potentials; Calcium dynamics;
Implementer(s): Chambers, Jordan [jordandchambers at gmail.com];
Search NeuronDB for information about:  I Na,p; I Na,t; I K,leak; I K,Ca; I CAN; I Mixed; I Na, leak; Ca pump;
{load_file("stdlib.hoc")}
celsius=36
{load_file("soma.hoc")}
access soma

//conductances
gnabar_nav17 = 20e-1
gbar_ih = 1e-4

proc default_var() {localobj s, pc
	s = new String()
	if (name_declared($s1) == 0) {
		if (argtype(2) == 2) {
			sprint(s.s, "~strdef %s", $s1)
			execute(s.s)
			sprint(s.s, "%s = \"%s\"", $s1, $s2)
		}else{
			hoc_ac_ = $2
			sprint(s.s, "%s = hoc_ac_", $s1)
		}
		execute(s.s)
	}
	pc = new ParallelContext()
	if (pc.id == 0) {
		sprint(s.s, "print \"%s  \", %s", $s1, $s1)
		execute(s.s)
	}
}

//integration time step
dt = 0.01
tstop = 1100

//inserting current clamp at soma
access soma
objectvar stim
stim = new IClamp(0.5)
stim.del = 100 
stim.dur = 500
///// change the amplitude to produce the different depolarising currents //////
stim.amp = -0.1

//for writing result files
objref vrec[1]
vrec[0] = new Vector()
{vrec[0].record(&soma.v(0.5), dt)}
objref tvec
tvec = new Vector()
{tvec.record(&t, dt)}
objref all
all = new File()
strdef datei

//graph
objref gmem
gmem = new Graph()
gmem.size(0, tstop, -100, 50)
{gmem.addvar("Membrane Potential", &soma.v(0.5), 2, 1)}
gmem.begin()

//defining some functions
proc run_sn() {
	soma v = -55.0
	finitialize()
	while (t < tstop) {
	    fadvance()
	    gmem.plot(t)
	}
	gmem.flush()
	write_file()
}

proc write_file() {
    sprint(datei, "./fig4mem.txt")
    all.wopen(datei)
    for i=0, vrec[0].size()-1 {
        all.printf("%g %g\n", tvec.x(i), vrec[0].x(i))
    }
    all.close
}

run_sn()
//quit()

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